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Signal Processing Letters, IEEE

Issue 5 • Date May 1997

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Displaying Results 1 - 10 of 10
  • Projection pursuit image compression with variable block size segmentation

    Page(s): 117 - 120
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (89 KB)  

    A novel multiresolution algorithm for lossy gray-scale image compression is presented. High-quality low bit rate image compression is achieved first by segmenting an image into regions of different sizes based on perceptual variation in each region and then constructing a distinct code for each block by using the theory of projection pursuit (PP). Projection pursuit allows one to adaptively construct a better approximation for each block by optimally selecting basis functions. The process is stopped when the desired peak signal-to-noise ratio (PSNR) or bit rate (b/pixel) is achieved. At rates below 0.5 b/pixel, our algorithm shows superior performance, both in terms of PSNR and subjective image quality, over the Joint Photographers Expert Group (JPEG) algorithm, and comparable performance to the embedded zerotree wavelet (EZW) algorithm. View full abstract»

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  • A compliant MPEG-1 layer II audio decoder with 16-b arithmetic operations

    Page(s): 121 - 122
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (55 KB)  

    A new 16-bit integer MPEG-1 layer II audio decoding algorithm is introduced, this algorithm incorporates a scaled Chen (1977) discrete cosine transform (DCT) instead of a generic DCT in the matrixing block, the use of a scaled DCT reduces the DCT multiply count by 28%. This 16-bit integer decoder is compliant with the Moving Picture Expert Group (MPEG) standard. View full abstract»

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  • Comments on the interpretation of instantaneous frequency

    Page(s): 123 - 125
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (92 KB)  

    Instantaneous frequency, taken as the derivative of the phase of the signal, is interpreted in the time-frequency literature as the average frequency of the signal at each time. We point out some difficulties with this interpretation, and show that for a generic two-component AM-FM signal, the interpretation holds only when the components are of equal strength. We conclude that instantaneous frequency and the average frequency at each time are generally two different quantities. One possible interpretation of the difference between these two quantities is suggested. View full abstract»

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  • On the minimum phase property of prediction-error polynomials

    Page(s): 126 - 127
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (56 KB)  

    We provide a simple proof of the minimum phase property of the optimum linear prediction polynomial. The proof follows directly from the fact that the minimized prediction error has to satisfy the orthogonality principle. Additional insights provided by this proof are also discussed. View full abstract»

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  • Decentralized nonparametric detectors

    Page(s): 128 - 131
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (124 KB)  

    A system formed by N identical nonparametric detectors and a fusion center is studied. The detectors transmit their decisions to the fusion center. The detectors are based either on the signs (sign test) or on the signs and the ranks of the observations (Wilcoxon test). It is concluded that the performance is almost unchanged when the product of the number of detectors by the number of samples received by each of them is constant. The asymptotic performance is also derived, and it is shown that it is equivalent to the centralized situation as the number of samples increases without limit. View full abstract»

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  • An approach to initializing the wavelet packet transform

    Page(s): 132 - 134
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (105 KB)  

    This article presents an approach to the initialization of the wavelet packet transform (WPT), which is a generalization of the discrete wavelet transform (DWT), by an extension of the interpolatory graphical display algorithm (IGDA). The exact computation of the WPT of functions that are piecewise constant on dyadic intervals is demonstrated. The method is for piecewise constant signals, as the details of how to do this do not appear to be readily available in the open literature. Furthermore, the solution is conveniently placed in a multirate signal processing framework. View full abstract»

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  • Subspace method for blind identification of multichannel FIR systems in noise field with unknown spatial covariance

    Page(s): 135 - 137
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (121 KB)  

    We present a new subspace-based method for blind identification of multichannel finite impulse response (FIR) systems. Instead of assuming spatially white additive noise as commonly used, we consider the case where the noise spatial covariance matrix is unknown. We show how a standard subspace method can be simply modified so that the channel estimate does not depend on the zero-lag correlation coefficient of the observation vector and, thus, is independent of the spatial covariance matrix of the additive noise. View full abstract»

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  • Blind identifiability of certain classes of multipath channels from second-order statistics using antenna arrays

    Page(s): 138 - 141
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (135 KB)  

    Recently, Ding (see IEEE Signal Processing Lett., vol.3, p.150-2, May 1996) has pointed out several classes of multipath channels that are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra. In this letter, we consider the blind identification problem using multiple antennas and show that the multipath channels will not give rise to any common roots among the subchannels formed from the antennas and, hence, they can be identified from second-order statistics. In our development, we will point out the role of band-limitedness of the channels in characterizing different classes. View full abstract»

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  • Joint angle and delay estimation using shift-invariance properties

    Page(s): 142 - 145
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (167 KB)  

    Assuming a multipath propagation scenario, we derive a closed-form subspace-based method for the simultaneous estimation of arrival angles and path delays from measured channel impulse responses, using knowledge of the transmitted pulse shape function and assuming a uniform linear array and uniform sampling. The algorithm uses a two-dimensional (2-D) ESPRIT-like shift-invariance technique to separate and estimate the phase shifts due to delay and direction-of-incidence, with automatic pairing of the two parameter sets. A straightforward extension to the multiuser case allows to connect rays to users as well. View full abstract»

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  • Fully static processor-optimal assignment of data-flow graphs

    Page(s): 146 - 148
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (94 KB)  

    The data-flow graph (DFG) is an important graph-theoretic model for multiprocessor implementation of real-time digital signal processing (DSP) algorithms. Given a time schedule for a DFG, we consider the problem of the processor-optimal assignment for a fully static schedule. Previously, the solution of this problem was found by solving an integer programming problem. We propose a linear programming approach to solving the problem. View full abstract»

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Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

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Meet Our Editors

Editor-in-Chief
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu